Service Scenarios Research Articles

Design, implementation and evaluation of a network-oriented service with environmental adaptability based on core/periphery structure

Many new network-oriented services have been developed in recent years, and they are expected to be virtualized in multi-access edge computing (MEC) environments, which are being standardized along with fifth generation (5 G). Because many new network-oriented services have been developed to meet various user requests, and service-oriented development, wherein service functions are divided and combined, is expected to facilitate the development of flexible services at low costs. A core/periphery structure is an information processing system in biological systems consisting of core units, that is densely connected and provide efficient process, and peripheral units that can accommodate a variety of inputs and outputs. In this paper, we introduce a core/periphery structure into the service design since the service based on this structure can adapt to various inputs and outputs with only modifying peripheral functions. We expect that development cost is reduced by designing services based on core/periphery structure, because the entire service is not modified against environmental changes. Besides, we also consider the balance between the penalty and the reduction of development costs since dividing functions and placing them in different devices creates extra communication paths and degrades service responsiveness. We designed and implemented two service scenarios for our shopping service with a remote robot based on a core/periphery structure. Using the implemented services, we show that the design using the core/periphery structure is effective in terms of implementation cost and overhead for information sharing among remote robots. Furthermore, we measured the penalty through experiments on actual devices and showed that it is tolerable.

Deep-reinforcement-learning-based range-adaptive distributed power control for cellular-V2X

A distributed congestion control must be adaptable to varying target communication ranges as cellular V2X (C-V2X) is evolving to support flexible coverage suitable for various service scenarios. This study proposes range-adaptive distributed power control (Ra-DPC) based on deep reinforcement learning (DRL) with the Monte Carlo policy gradient algorithm. A key finding is that the agents learn Ra-DPC more effectively when the cumulative interference power of the subchannels is adopted as the state of the DRL model, rather than the channel busy ratio. The proposed Ra-DPC algorithm performs better in energy efficiency and packet delivery ratio than the existing technologies.

Robot task programming in complex task scenarios based on spatio-temporal constraint calculus

PurposeRobots face fundamental challenges in achieving reliable and stable operations for complex home service scenarios. This is one of the crucial topics of robotics methods to imitate human beings’ advanced cognitive characteristics and apply them to solve complex tasks. The purpose of this study is to enable robots to have the ability to understand the scene and task process in complex scenes and to provide a reference method for robot task programming in complex scenes.Design/methodology/approachThis paper constructs a task modeling method for robots in complex environments based on the characteristics of the perception-motor memory model of human cognition. In the aspect of episodic memory construction, the task execution process is included in the category of qualitative spatio-temporal calculus. The topology interaction of objects in a task scenario is used to define scene attributes. The task process can be regarded as changing scene attributes on a time scale. The qualitative spatio-temporal activity graphs are used to analyze the change process of the object state with time during the robot task execution. The tasks are divided according to the different values of scene attributes at different times during task execution. Based on this, in procedural memory, an object-centered motion model is developed by analyzing the changes in the relationship between objects in the scene episode by analyzing the scene changes before and after the robot performs the actions. Finally, the task execution process of the robot is constructed by alternately reconstructing episodic memory and procedural memory.FindingsTo verify the applicability of the proposed model, a scenario where the robot combines the object (one of the most common tasks in-home service) is set up. The proposed method can obtain the landscape of robot tasks in a complex environment.Originality/valueThe robot can achieve high-level task programming through the alternating interpretation of scenarios and actions. The proposed model differs from traditional methods based on geometric or physical feature information. However, it focuses on the spatial relationship of objects, which is more similar to the cognitive mechanism of human understanding of the environment.

The Progress and Prospects in the Scenario Simulation Research on the Sustainability of Regional Ecosystem Services Based on a “Safe Operating Space”

Integrating scenarios and models to assess the sustainability of future regional ecosystem services is at the forefront of ecosystem service science. However, there are a lack of comprehensive reviews on this topic. Therefore, this study provides a systematic review of the research progress considering two aspects: ecosystem service scenario simulation and sustainability assessments based on the concept of a “safe operating space.” We found that (1) a number of studies have already started to explore methods for evaluating the sustainability of future ecosystem services; (2) in terms of scenario construction methods, most existing studies have adopted the global classical scenario downscaling approach, while less consideration has been given to the important socio-economic-environmental characteristics of a region itself, which affect the credibility and policy relevance of scenarios; and (3) in terms of sustainability simulation evaluation, most existing studies are qualitative comparisons of the sustainability of ecosystem services within different scenarios, while quantitative methods are lacking. We proposed an approach that combined participatory scenario construction and a regional safe operating space to address the above identified challenges. Successfully implementing this research approach would provide decision makers with more accurate and practical early warning information regarding the sustainability of future ecosystem services.

The Drucker–Prager criterion-based plasticity theory of amorphous alloys under the complex stress states

The constitutive models of materials are pushed to their limits in a wide range of service scenarios, each with a unique stress state, strain rate, and temperature coupling. This paper successfully captured the stress state sensitivity of amorphous alloys using the free volume theory and the Drucker–Prager yield criterion. The varying yield surface and shear band angle as the dilation coefficient changes are well captured by the FEM simulations. The model can also accurately portray the influence of the stress state, as well as the difference of shear-induced dilation between the tension and compression. This model can facilitate the application of amorphous alloys in complicated local stress states at a large scale and structural level, such as in chiral mechanical metamaterials and gear structures.

Task space control for on-orbit space robotics using a new ROS-based framework

This paper proposes several task space control approaches for complex on-orbit high degrees of freedom robots. These approaches include redundancy resolution and take the non-linear dynamic model of the on-orbit robotic systems into account. The suitability of the proposed task space control approaches is explored in several on-orbit servicing operations requiring visual servoing tasks of complex humanoid robots. A unified open-source framework for space-robotics simulations, called OnOrbitROS, is used to evaluate the proposed control systems and compare their behaviour with state-of-the-art existing ones. The adopted framework is based on ROS and includes and reproduces the principal environmental conditions that eventual space robots and manipulators could experience in an on-orbit servicing scenario. The architecture of the different software modules developed and their application on complex space robotic systems is presented. Efficient real-time implementations are achieved using the proposed OnOrbitROS framework. The proposed controllers are applied to perform the guidance of a humanoid robot. The robot dynamics are integrated into the definition of the controllers and an analysis of the results and practical properties are described in the results section.

“Touch over tech”: a longitudinal examination of human touch along a travel journey

PurposeWhile the importance of human touch for maintaining a tech–touch balance has been stressed, little knowledge exists regarding how such human elements should be incorporated in service settings dominated by technologies. This study aims to examine the outcomes of human touch levels across different travel stages in a hotel stay context.Design/methodology/approachData were collected through a survey on 900 participants. Latent class analysis was first conducted to categorize the sample into groups based on human touch levels. Hypotheses were then tested using regression-based moderation analysis with the PROCESS macro for SPSS.FindingsHuman touch level negatively predicts perceived risk, which is negatively associated with satisfaction. These effects are particularly significant at check-in and check-out stages. Informational privacy significantly moderates the effect of human touch level on perceived risk. Such interaction effects were spotted at the booking and check-out stages.Research limitations/implicationsThis study contributes to theory by revealing the role of human touch elements in technology-driven service scenarios and provides practical guidelines for hotels on sharpening service experience by integrating human touch and technology elements.Originality/valueThrough integrating the service encounter framework and concept of customer touchpoints, this study takes a different approach that integrates both “tech” and “touch” by investigating the effects of customer-owned touchpoints in each core stage of a hotel stay journey.

The impact of popularity cues on consumer effort for making experiential purchases: A study within the context of hospitality services

PurposeBased on the framework of social influence theory, this paper aims to explore the influence of popularity cues on consumer effort for making experiential purchases, as well as to examine the mediating role of conversational potential and the moderating role of consumer susceptibility to interpersonal influence (CSII). Design/methodology/approachA simple random sampling method was used to recruit participants from Chinese online survey platforms with a final total sample size of 371 participants for three experiments. Taking an experimental approach, this paper tests the proposed hypotheses by conducting three online experiments based on hospitality service scenarios. The data analyses were carried out using SPSS 25.0 software. Specifically, the effect of popularity cues on consumer effort was verified via a one-way ANOVA; the mediating role of conversation potential was analyzed using PROCESS Model 4; and the moderating role of CSII was tested using PROCESS Model 7. FindingsThe presence of popularity cues significantly increases conversational potential and consumer effort in acquiring hospitality services. The impact of popularity cues on consumer effort is mediated by conversational potential. The relationship between popularity cues and conversational potential is moderated by CSII. Specifically, the effect of popularity cues on conversational potential is only observable in high-CSII consumers. Originality/valueTo date, limited research has been conducted on the antecedent variables of consumer effort. This paper contributes to the existing literature on popularity cues and consumer effort by examining the effectiveness of popularity cues in motivating consumer effort and exploring its boundary conditions. This study empirically validates the proposed model and provides suggestions for future research and practical applications in hospitality services.

A novel multiple access communication protocol for LoRa networks without LoraWAN

Current <span>studies predict there will be approximately 75 billion internet of things (IoT) devices connected to the internet by 2025. Such enormous IoT networks will require efficient communications systems to support those networks running well. We consider one of the emerging communications technologies that is widely used for wireless wide-area network, i.e., long range (LoRa). By default, LoRa wide area networking (LoRaWAN) has been equipped with a medium access control (MAC) protocol, however, several studies showed that LoRaWAN might not be the most excellent choice for certain applications of low-power wide area network, for example, peer-to-peer and mesh networks. In this work, we propose an application layer LoRa multi-communication (LMC) protocol to resolve multiple access problems in LoRa networks without employing LoRaWAN. The algorithm was embedded and tested on energy-constraint devices as building blocks of most IoT systems. Our examination in a controlled environment showed that the proposed algorithm achieved 94% averaged packet reception ratio (PRR) and 33.3 hours longer averaged battery lifetime compared to the default operation (without LMC algorithm) of LoRa networks. The proposed algorithm also introduced longer averaged time on air (ToA) compared to the default LoRa network mainly due to its best-effort service scenario applied to the proposed algorithm.</span>

Integrating ATM and air transport into multimodal transport system for Door-to-Door travel: the X-TEAM D2D project proposed approach

The project X-TEAM D2D (Extended ATM for Door-to-Door Travel) has been funded by SESAR JU in 2020 and completed its activities in 2022, pursuing and accomplishing the definition, development and initial assessment of a Concept of Operations (ConOps) for the seamless integration of ATM and air transport into an overall intermodal network, including other available transportation means (surface, water), to support the door-to-door connectivity, in up to 4 hours, between any location in Europe. The project addressed the ATM and air transport, including Urban Air Mobility (UAM), integration in the overall transport network serving urban and extended urban (up to regional level) mobility, specifically identifying and considering the transportation and passengers service scenarios expected for the near, medium and long-term future, i.e. for the project baseline (2025), intermediate (2035) and final (2050) time horizons. In this paper, the main outcomes from the project activities are summarized, with particular emphasis on the studies about the definition of future scenarios and use cases for the integration of the vertical transport with the surface transport towards integrated intermodal transport system and about identification of the barriers towards this goal. In addition, an outline is provided on the specific ConOps for the integration of ATM in intermodal transport infrastructure (i.e. the part of the overall ConOps devoted to integration of different transportation means) and on the specific ConOps for the integration of ATM in intermodal service to passengers (i.e. the specific component of the ConOps devoted to design of a unique service to passengers). Finally, the main outcomes are summarized from the validation of the proposed ConOps through dedicated simulations.

Experimental Evaluation of an IoT-Based Platform for Maritime Transport Services

In recent years, the adoption of innovative technologies in maritime transport and logistics systems has become a key aspect towards their development and growth, especially due to the complex and heterogeneous nature of the maritime environment. On the other hand, Internet of Things (IoT) solutions are gaining importance in the shipping industry thanks to the huge number of distributed cameras and sensors in modern ships, cargoes and sea ports, which can be exploited to improve safety, costs and productivity. This paper presents an experimental evaluation of a maritime platform, which enables a wide range of 5G-based services in the context of logistics and maritime transportation. Its core is a Narrow Band (NB)-IoT framework used to run massive IoT services on top of a hybrid terrestrial–satellite network and feed a OneM2M platform with significant data on maritime transport to develop high-level and value-added logistic applications on top. Among the many different services that could be provided by the maritime platform, we focus on the cargo-ship container tracking use case through the Global Tracking System, which allows for continuous container monitoring all over the seas in a port-to-port service scenario. The results of the experimental tests illustrate the capacity of the platform in managing the high number of messages transmitted by the container tracking devices (i.e., more than 3000) and its efficiency in limiting the average maximum latency and packet loss below 5.5 s and 0.9%, respectively.

Green Inspired Service Consumption: The Gen Z Consumer’s Perspective

This study assesses moderated mediation effects of both cognitive factors and emotions influencing the linkage between service greenness and Gen Z’s purchase intentions. Using data from 612 observations pooled across multiple studies and service scenarios, the findings affirm that emotions mediate the relationship between service greenness and purchase intent. Additionally, Gen Z consumers with greener consumption values show a stronger emotional connection to service greenness. Surprisingly, the findings show a stronger emotional connection for a more functional service and gender had no moderating effect. The findings contribute to service theory and assist managers with reaching Gen Z more effectively.

Usage of digital library services during COVID-19 pandemic: a study of Indian Institutes of Management (IIMs)

PurposeThis paper aims to find out the digital services of management libraries provided during the library closure and the challenges and initiatives the libraries have taken up to fulfill the need of their user community during the pandemic crisis.Design/methodology/approachTo meet the purpose of the study, the investigators have used a survey method. An online questionnaire was devised and administered among the Indian Institutes of Management (IIMs) librarians using Microsoft Forms.FindingsThe study's findings suggested that all the libraries under investigation must avail of various digital library services in the wake of the coronavirus pandemic. Further, the investigators recommend that libraries formulate a disaster preparedness and management plan in the wake of the COVID-19 pandemic so that libraries can prepare themselves for the future.Originality/valueThe pandemic has affected every aspect of life and changed the digital library services scenario. Thus, it is essential to examine the role libraries have played during the COVID-19 pandemic and distinguish the challenges and initiatives libraries have taken to tackle the problems they faced. This study has been conducted on the digital library services that were provided by the libraries of IIMs.

Evaluation and analysis of tunnel lighting service status based on driving safety

Objective The service status of tunnel lighting has an important impact on driving safety. Existing research mainly discussed the impact of a single evaluation indicator of lighting service status on driving safety and paid less attention to the impact of multiple evaluation indicators on driving safety. Methods In this research, field tests of tunnels in three speed scenarios and 52 service scenarios are completed. DIALux software was selected to simulate more intensive illuminance, which could be used to calculate U0 , U1 , qc , and C. Using U0 , U1 , qc , and C as explanatory variables, and applying the normalized visual recognition results as explained variables, ordinary least squares regression (OLS) was performed to calculate the influence weight of each explanatory variable on driving safety. Results The results show that the four independent variables occupied different weights under different working conditions. However, on the whole, U0 and U1 occupied a greater weight. The weight of C lies between qc and U0 , and U1 and qc occupied the smallest weight in all scenarios. Locally, U0 was greater than U1 , with the exception when the illumination attenuation value was 70%. Conclusions The influence of the total uniformity of the road surface luminance and longitudinal uniformity of the road centerline luminance on driving safety was significantly greater than the influence of the contrast revealing coefficient and luminance contrast C on driving safety. When the luminous flux was attenuated to 70% or less and when the number of failed lamps was at least four, the lighting quality would be significantly reduced, which would substantially affect driving safety.

Study of Resource Allocation for 5G URLLC/eMBB-Oriented Power Hybrid Service.

With the rapid development of the 5G power Internet of Things (IoT), new power systems have higher requirements for data transmission rates, latency, reliability, and energy efficiency. Specifically, the hybrid service of enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) has brought new challenges to the differentiated service of the 5G power IoT. To solve the above problems, this paper first constructs a power IoT model based on NOMA for the mixed service of URLLC and eMBB. Considering the shortage of resource utilization in eMBB and URLLC hybrid power service scenarios, the problem of maximizing system throughput through joint channel selection and power allocation is proposed. The channel selection algorithm based on matching as well as the power allocation algorithm based on water injection are developed to tackle the problem. Both theoretical analysis and experimental simulation verify that our method has superior performance in system throughput and spectrum efficiency.

To evaluate the use and clinical effect of intermittently scanned continuous glucose monitoring in adults with type 1 diabetes: Results of a multicentre study

AimTo evaluate the use and clinical effect of intermittently scanned continuous glucose monitoring (isCGM) in adults with type 1 diabetes (T1D) in a public health service scenario. MethodCross-sectional retrospective analysis of all patients with T1D and medical indication for isCGM use from a cohort followed since 2010 at Castilla-La Mancha Public Health Service (Spain). Primary outcome was HbA1c change during the first year of follow-up after isCGM initiation. Secondary outcomes included evaluation of self-monitoring of blood glucose (SMBG), isCGM and insulin use, along with glycometric indexes. ResultsA total of 945 T1D patients were analyzed. Median age was 49.5 years (IQ range 19.0 years) and T1D duration of 28.9 years (IQ range 14.0 years). The most frequent insulin therapy alternatives were multiple daily injections (85%) followed by insulin pump (11%). Eighty percent of the patients were active isCGM users with a 90% of adherence to the device. Patients showed a mean daily scan frequency of 10.1±6.4scans/day. Daily SMBG reduced by −3.5 test/day [95% CI −3.7, −3.2; P<0.001]. We detected an HbA1c reduction of −0.3% (−4mmol/mol) [95% CI −0.2, −0.4 (−3, −5); P<0.001] at the end of the follow-up. An inverse correlation between HbA1c levels at the end of the follow-up and daily frequency of isCGM scanning (R=−0.34, P<0.001) was observed. Dropout rate was 4%, and 4% of patients were not willing to use isCGM. ConclusionsAdult patients with T1D improved glycaemic control after isCGM initiation in a public health service scenario. Despite described clinical benefits, a higher than expected percentage of patients were not using isCGM technology. NCT05095610.

A Literature Review of Big Data and Metadata Management Systems

Abstract: Metadata is essential for the successful operation of data files, as it acts as the underlying data that helps maintain and manage the namespace, permissions, and address of the file data blocks. The performance of metadata services has a direct impact on the overall performance of the file system, as these operations can account for a significant portion, up to 80%, of file system activity. Large-scale distributed file systems (DFS) have emerged to meet the rising demand for data storing. These systems provide users with access to numerous storage units spread across various locations. The widespread use of large-scale DFSs as the foundation for a range of computing systems and applications, particularly in the era of Big Data, highlights the importance of efficient metadata management. This paper seeks to offer an enhanced knowledge of the current status of metadata systems in large-scale DFSs, this paper presents a comprehensive overview of the latest research in the field. DFSs are defined by three aspects: scalability, performance, and availability. Moreover, the study evaluates various challenges and limitations in the current research, providing valuable insight for future studies. Overall, the study attempts to give a complete knowledge of the present scenario of metadata services across large-scale DFSs and to recommend areas for future research and development.

A novel neural network model fusion approach for improving medical named entity recognition in online health expert question-answering services

Because of the frequent occurrence of chronic diseases, the COVID-19 pandemic, etc., online health expert question-answering (HQA) services have been unable to cope with the rapidly increasing demand for online consultations. Building a virtual health assistant based on medical named entity recognition (NER) can effectively assist with the consultation process, but the unstandardized expressions within HQA text pose a serious challenge for medical NER tasks. The main goal of this study is to propose a novel deep medical NER approach based on a collaborative decision strategy (CDS), i.e., co_decision_NER (CDN), that can identify standard and nonstandard medical entities in the HQA context. We collected 10,000 question–answer pairs from HaoDF, extracted medical entities from 15 entity categories, and used a CDS to fuse the advantages of different NER models. Ultimately, CDN achieved a performance (precision = 84.50%, recall = 84.30%, F1 = 84.40%) that was significantly better than that of the state-of-the-art (SOTA) method. Our empirical analysis suggests that the entity types Disease (DIS), Sign (SIG), Test (TES), Drug (DRU), Surgery (SUR), Precaution (PRE), and Region (REG) can be most easily expressed arbitrarily in the doctor–patient interaction scenario of HQA services. In addition, CDN can identify not only standard but also nonstandard medical entities, effectively alleviating the severe out-of-vocabulary (OOV) problem faced by HQA services when performing medical NER tasks. The core contribution of this study is the development of a novel neural network model fusion algorithm that can improve the performance of entity recognition in medical domain-specific tasks.

P2P Cloud Manufacturing Based on a Customized Business Model: An Exploratory Study

To overcome the problems of long production cycle and high cost in the product manufacturing process, a P2P (platform to platform) cloud manufacturing method based on a personalized custom business model has been proposed in this paper by integrating different technologies such as deep learning and additive manufacturing (AM). This paper focuses on the manufacturing process from a photo containing an entity to the production of that entity. Essentially, this is an object-to-object fabrication. Moreover, based on the YOLOv4 algorithm and DVR technology, an object detection extractor and a 3D data generator are constructed, and a case study is carried out for a 3D printing service scenario. The case study selects online sofa photos and real car photos. The recognition rates of sofa and car were 59% and 100%, respectively. Retrograde conversion from 2D data to 3D data takes approximately 60 s. We also carry out personalized transformation design on the generated sofa digital 3D model. The results show that the proposed method has been validated, and three unindividualized models and one individualized design model have been manufactured, and the original shape is basically maintained.

Will Social Distancing in Service Encounters Affect Consumers' Value Perception During the COVID-19 Pandemic? The Role of Servicescape, Self-Efficacy, and Technological Intervention.

This study investigates how physical and psychological distance from one's surroundings may influence one's perception of connectedness with the servicescape and, ultimately, perception of value. It also examines the effect of consumers' techno-psychological differences and interaction modes on this distance-closeness relationship. The researchers develop and test a conceptual framework of how personal cognitive traits and technological intervention may alter consumers' perceived connectedness to the servicescape and influence their perceived value in different service settings. Via a quasi-experiment design in three service scenarios, this research shows a synthetical effect of contactless technology in the distancing setting that may work more effectively on high self-efficiency customers to change their perceived closeness to the servicescape and further change their evaluation of the service. The findings reveal the practical implications of social distancing for different types of consumers in service encounters during or after the COVID-19 pandemic.